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Record W1979571796 · doi:10.1002/app.30925

Value‐added derivatives of soda lignin Alfa grass (<i>Stipa tenacissima</i>). II. Uses as lubricants in plastic processing

2009· article· en· W1979571796 on OpenAlexaff
H. Nadji, Denis Rodrigue, Ahmed Benaboura, Yves Bédard, Tatjana Stevanović, Bernard Riedl

Bibliographic record

VenueJournal of Applied Polymer Science · 2009
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsZinc stearateMaterials scienceStearic acidRaw materialPulp (tooth)PolyethyleneZincLigninChemical engineeringComposite materialOrganic chemistryChemistryMetallurgy

Abstract

fetched live from OpenAlex

Abstract Esparto ( Stipa tenacissima ) grass, also called Alfa is the raw material for the manufacture of paper pulp in North Africa. To add value to one of its processing by‐products, we aimed to develop lubricants from modified Soda‐Lignin (SL), which could eventually compete with industrial lubricants such as zinc stearates. Linear low density polyethylene mixed formulations prepared with zinc stearate and each modified lignin was studied by rheological tests using a rotational parallel plate system to investigate the effects of such esterified SL additives. One type, made up of SL esterified with 100% stearic anhydride (W/W) was found to promote excellent external lubrication. The same result was confirmed by contact angle and thermal analysis. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.227
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2009
Admission routes1
Has abstractyes

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